Inversions of the LVS3 model provide physically-based descriptions of fPARchl, the amount of light absorbed by chlorophyll, from MODIS images. Summertime fPARchl, near Utqiagvik (Barrow), AK shows a greening trend but the ecosystem has not yet reached a tipping point and can still return to its original state.

References:

Technical Description of Figures

Figure: Images for area around Utqiagvik (Barrow), AK from MODIS for Aug. 11, 2004, a date near maximum greenness for this region. Upper left is Normalized Difference Vegetation Index (NDVI), an index used to map vegetation using MODIS bands 1 and 2. The other images are derived from inversions of the physically based LVS3 model*, showing distributions of the fraction of photosynthetically active radiation absorbed by all (living and dead) vegetation (fAPARtotal), the fraction of photosynthetically active radiation absorbed by chlorophyll (fAPARchl), and the fraction coverage of surface water. All images use the same color scale, shown next to the fraction of surface water image. The bottom right plot shows the change in summertime fAPARchl averaged between days 200 through 248, and the black line is a linear regression showing the overall trend in these data.

How are high latitude ecosystems responding to high rates of climate change? Previous work has examined time change in the spectral index NDVI. However, NDVI, particularly for high latitude ecosystems, is affected by a number of non-vegetation factors, including: frequently small solar elevation angles, variations in viewing angles, varying amounts of snow, water, and bare ground cover, and relatively large proportions of non-green materials (e.g., standing dead vegetation) in the canopy. We used inversions of the LVS3 model to provide physically-based descriptions of fAPARchl, the amount of light absorbed by chlorophyll, a descriptor of photosynthetic potential, from MODIS imagery. This approach utilizes spectral information from all MODIS land bands, instead of only two bands used by the NDVI, and explicitly addresses solar and view angles as well as determining water cover, snow cover, and bare ground cover, all factors that affect NDVI. The images show significant differences between NDVI and fAPARchl for the area around Utqiagvik (Barrow), AK.

Summertime fAPARchl shows a general greening trend, with increasing fAPARchl over the period from 2001 to 2014. However, from 2013 to 2014 the fAPARchl dropped from its largest to its smallest value over the study period, indicating that while responding to warming conditions this ecosystem has not yet reached a tipping point and can still return to its original state.

Variation of snow melt discharge modeled using the University of New Hampshire Water Balance Model, which is capable of tracking snow and glacier runoff separately. The results not only show the seasonal variation of available snow melt in the rivers, but also how much water is used up-stream.

Data Sources:

ERA-Interim, MERRA2, COAWST simulation for HMA by S. Nichols (GSFC).

Technical Description of Figures

Figure 1: Amount of snow melt in river basins at the peak melt season, on May 15th 1980. The units are in m3/sec. Note the large amount of snow water used in the upper basins especially Indus Basin to the west.

Figure 2: Amount of snow melt in river basins on October 15th, 1980.

Figure 3: The annual variation of total snowmelt in Indus basin, and discharge due to snowmelt at the mouth of Indus river. Units are in km3/year. Note the significant lack of snow-melt reaching the mouth of the river due to antropogenic (e.g. agricultural) activities in upper Indus Basin.

Through our High Mountain Asia (HMA) project, we study the region in a wholistic pattern to better understand the dynamics of HMA glaciers, and how a changing climate will impact the downstream regions that are dependent on the glacier and snowmelt runoff. Through this effort we can model what the water availability in the future will be like, and how it will impact the agricultural activities downstream. Our preliminary results indicate an increase in water availability up to year 2050 or so, after which the water resources become less available due to reduced glacier area.